Building a FHIR-native health data platform on Databricks Lakebase

Summary

Healthcare organizations often keep a FHIR server, analytics warehouse, and ETL pipelines separate, replicating clinical data and fragmenting governance. The proposed architecture standardizes incoming HL7v2, C-CDA, X12, and proprietary data into FHIR using Health Samurai converters, terminology normalization, MDM/MPI deduplication, and Implementation Guide validation. Aidbox, Health Samurai's FHIR server and database, runs on Databricks Lakebase, while Moonlink synchronizes operational and analytical formats without ETL. This exposes one governed dataset through Spark, SQL, ML, AI/BI, FHIR API, SMART on FHIR, and SQL on FHIR ViewDefinitions. The architecture supports use cases including EHR optimization, value-based care, member engagement, and compliance capabilities, with insights connected to clinician and billing workflows through SMART on FHIR and CDS Hooks.

Context

Healthcare data is distributed across EHRs, claims, labs, pharmacy, SDoH, HL7v2 messages, C-CDA documents, X12 transactions, and proprietary formats. Separate FHIR servers, analytics warehouses, and ETL pipelines duplicate data, access controls, audit trails, and compliance work while limiting analytical and AI access.

Approach / What changed

Health Samurai standardizes source data into FHIR using converters, terminology normalization, MDM/MPI, and FHIR Implementation Guide validation. Aidbox runs natively on Databricks Lakebase, with Moonlink synchronizing operational and analytical formats without ETL so Databricks tools and standards-based interfaces access the same governed dataset.

Takeaways

• Health Samurai uses HL7v2, C-CDA, and X12 converters, terminology systems including LOINC and SNOMED CT, MDM/MPI, and FHIR Implementation Guides to produce standardized data and a single golden record per patient.
• Aidbox runs on Databricks Lakebase, a fully managed, serverless Postgres database integrated into the Databricks Data + AI Platform; Moonlink provides real-time synchronization without ETL.
• The platform offers Databricks-native access through Spark, SQL, ML, and AI/BI alongside standards-based access through FHIR API, SMART on FHIR, and SQL on FHIR ViewDefinitions.

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